Investigating the consistency between proxy-based reconstructions and climate models using data assimilation: a mid-Holocene case study

The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.

A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Seismic anisotropy in the Morcles nappe shear zone: Implications for seismic imaging of crustal scale shear zones

Microstructures and textures of calcite mylonites from the Morcles nappe large-scale shear zone in southwestern Switzerland develop principally as a function of 1) extrinsic physical parameters including temperature, stress, strain, strain rate and 2) intrinsic parameters, such as mineral composition. We collected rock samples at a single location from this shear zone, on which laboratory ultrasonic velocities, texture and microstructures were investigated and quantified. The samples had different concentration of secondary mineral phases (< 5 up to 40 vol.%). Measured seismic P wave anisotropy ranges from 6.5% for polyphase mylonites (~ 40 vol.%) to 18.4% in mylonites with < 5 vol.% secondary phases. Texture strength of calcite is the main factor governing the seismic P wave anisotropy. Measured S wave splitting is generally highest in the foliation plane, but its origin is more difficult to explain solely by calcite texture. Additional texture measurements were made on calcite mylonites with low concentration of secondary phases (≤ 10 vol.%) along the metamorphic gradient of the shear zone (15 km distance). A systematic increase in texture strength is observed moving from the frontal part of the shear zone (anchimetamorphism; 280 °C) to the higher temperature, basal part (greenschist facies; 350–400 °C). Calculated P wave velocities become increasingly anisotropic towards the high-strain part of the nappe, from an average of 5.8% in the frontal part to 13.2% in the root of the basal part. Secondary phases raise an additional complexity, and may act either to increase or decrease seismic anisotropy of shear zone mylonites. In light of our findings we reinterpret the origin of some seismically reflective layers in the Grône–Zweisimmen line in southwestern Switzerland (PNR20 Swiss National Research Program). We hypothesize that reflections originate in part from the lateral variation in textural and microstructural arrangement of calcite mylonites in shear zones.

Present state of global wetland extent and wetland methane modelling: methodology of a model inter-comparison project (WETCHIMP)

The Wetland and Wetland CH4 Intercomparison of Models Project (WETCHIMP) was created to evaluate our present ability to simulate large-scale wetland characteristics and corresponding methane (CH4) emissions. A multi-model comparison is essential to evaluate the key uncertainties in the mechanisms and parameters leading to methane emissions. Ten modelling groups joined WETCHIMP to run eight global and two regional models with a common experimental protocol using the same climate and atmospheric carbon dioxide (CO2) forcing datasets. We reported the main conclusions from the intercomparison effort in a companion paper (Melton et al., 2013). Here we provide technical details for the six experiments, which included an equilibrium, a transient, and an optimized run plus three sensitivity experiments (temperature, precipitation, and atmospheric CO2 concentration). The diversity of approaches used by the models is summarized through a series of conceptual figures, and is used to evaluate the wide range of wetland extent and CH4 fluxes predicted by the models in the equilibrium run. We discuss relationships among the various approaches and patterns in consistencies of these model predictions. Within this group of models, there are three broad classes of methods used to estimate wetland extent: prescribed based on wetland distribution maps, prognostic relationships between hydrological states based on satellite observations, and explicit hydrological mass balances. A larger variety of approaches was used to estimate the net CH4 fluxes from wetland systems. Even though modelling of wetland extent and CH4 emissions has progressed significantly over recent decades, large uncertainties still exist when estimating CH4 emissions: there is little consensus on model structure or complexity due to knowledge gaps, different aims of the models, and the range of temporal and spatial resolutions of the models.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

Are cryptic host species also cryptic to parasites? Host specificity and geographical distribution of acanthocephalan parasites infecting freshwater Gammarus

Many parasites infect multiple host species. In coevolving host–parasite interactions, theory predicts that parasites should be adapted to locally common hosts, which could lead to regional shifts in host preferences. We studied the interaction between freshwater Gammarus (Crustacea, Amphipoda) and their acanthocephalan parasites using a large-scale field survey and experiments, combined with molecular identification of cryptic host and parasite species. Gammarus pulex is a common host for multiple species of Acanthocephala in Europe but, in Switzerland, is less common than two cryptic members of the Gammarus fossarum species complex (type A and type B). We found that natural populations of these cryptic species were frequently infected by Pomphorhynchus tereticollis and Polymorphus minutus. Four additional parasite species occurred only locally. Parasites were more common in G. fossarum type B than in type A. Infection experiments using several host and parasite sources confirmed consistently lower infection rates in G. pulex than in G. fossarum type A, suggesting a general difference in susceptibility between the two species. In conclusion, we could show that cryptic host species differ in their interactions with parasites, but that these differences were much less dramatic than differences between G. fossarum (type A) and G. pulex. Our data suggest that the acanthocephalans in Switzerland have adapted to the two most common Gammarus species in this region where host species frequencies differ from near-by regions in Europe.

Dependence of Eemian Greenland temperature reconstructions on the ice sheet topography

The influence of a reduced Greenland Ice Sheet (GrIS) on Greenland's surface climate during the Eemian interglacial is studied using a set of simulations with different GrIS realizations performed with a comprehensive climate model. We find a distinct impact of changes in the GrIS topography on Greenland's surface air temperatures (SAT) even when correcting for changes in surface elevation, which influences SAT through the lapse rate effect. The resulting lapse-rate-corrected SAT anomalies are thermodynamically driven by changes in the local surface energy balance rather than dynamically caused through anomalous advection of warm/cold air masses. The large-scale circulation is indeed very stable among all sensitivity experiments and the Northern Hemisphere (NH) flow pattern does not depend on Greenland's topography in the Eemian. In contrast, Greenland's surface energy balance is clearly influenced by changes in the GrIS topography and this impact is seasonally diverse. In winter, the variable reacting strongest to changes in the topography is the sensible heat flux (SHF). The reason is its dependence on surface winds, which themselves are controlled to a large extent by the shape of the GrIS. Hence, regions where a receding GrIS causes higher surface wind velocities also experience anomalous warming through SHF. Vice-versa, regions that become flat and ice-free are characterized by low wind speeds, low SHF, and anomalous low winter temperatures. In summer, we find surface warming induced by a decrease in surface albedo in deglaciated areas and regions which experience surface melting. The Eemian temperature records derived from Greenland proxies, thus, likely include a temperature signal arising from changes in the GrIS topography. For the Eemian ice found in the NEEM core, our model suggests that up to 3.1 °C of the annual mean Eemian warming can be attributed to these topography-related processes and hence is not necessarily linked to large-scale climate variations.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

[The effectiveness of rare earth elements as a possible alternative growth promoter for pigs and poultry].

Mixtures of Rare Earth Elements (REE) have been used as animal growth-promoters on a large scale in China during the last 20 years. Numerous studies carried out in China claim it produces quite sensational growth-promoting effects in all categories of farm animals. To explore the question of whether REE's might prove suitable as a growth-promoter under western keeping conditions, feeding experiments were performed on pigs and poultry. The animals received a typical diet, supplemented with REE salts in concentrations between 75 and 300 mg/kg feed. Weight-gain, feed-intake, feed-conversion and (where applicable) laying parameters were observed. It was shown that in pigs receiving feed supplemented with REEs, an increase in daily weight gain of up to 19% and an improvement in feed-conversion of up to 11% can be achieved, whereas, for poultry, no positive effects on growth or productivity of the animals could be observed. Testing of important organs via Neutron Activating Analysis (NAA) showed a minute accumulation of REE, principally in liver and bones. Analysis of the poultry gut-flora, using selective media, showed that the main microorganism populations of the alimentary canal were unaffected by feed-supplementation with REE.

Neutrino physics with multi-ton scale liquid xenon detectors

We study the sensitivity of large-scale xenon detectors to low-energy solar neutrinos, to coherent neutrino-nucleus scattering and to neutrinoless double beta decay. As a concrete example, we consider the xenon part of the proposed DARWIN (Dark Matter WIMP Search with Noble Liquids) experiment. We perform detailed Monte Carlo simulations of the expected backgrounds, considering realistic energy resolutions and thresholds in the detector. In a low-energy window of 2–30 keV, where the sensitivity to solar pp and 7Be-neutrinos is highest, an integrated pp-neutrino rate of 5900 events can be reached in a fiducial mass of 14 tons of natural xenon, after 5 years of data. The pp-neutrino flux could thus be measured with a statistical uncertainty around 1%, reaching the precision of solar model predictions. These low-energy solar neutrinos will be the limiting background to the dark matter search channel for WIMP-nucleon cross sections below ~2X 10-48 cm2 and WIMP masses around 50 GeV c 2, for an assumed 99.5% rejection of electronic recoils due to elastic neutrino-electron scatters. Nuclear recoils from coherent scattering of solar neutrinos will limit the sensitivity to WIMP masses below ~6 GeV c-2 to cross sections above ~4X10-45cm2. DARWIN could reach a competitive half-life sensitivity of 5.6X1026 y to the neutrinoless double beta decay of 136Xe after 5 years of data, using 6 tons of natural xenon in the central detector region.

Experimental validation of a nonlinear μ FE model based on cohesive-frictional plasticity for trabecular bone

Trabecular bone is a porous mineralized tissue playing a major load bearing role in the human body. Prediction of age-related and disease-related fractures and the behavior of bone implant systems needs a thorough understanding of its structure-mechanical property relationships, which can be obtained using microcomputed tomography-based finite element modeling. In this study, a nonlinear model for trabecular bone as a cohesive-frictional material was implemented in a large-scale computational framework and validated by comparison of μFE simulations with experimental tests in uniaxial tension and compression. A good correspondence of stiffness and yield points between simulations and experiments was found for a wide range of bone volume fraction and degree of anisotropy in both tension and compression using a non-calibrated, average set of material parameters. These results demonstrate the ability of the model to capture the effects leading to failure of bone for three anatomical sites and several donors, which may be used to determine the apparent behavior of trabecular bone and its evolution with age, disease, and treatment in the future.

Impact of oceanic circulation changes on atmospheric δ¹³ CO₂

δ¹³ CO₂ measured in Antarctic ice cores provides constraints on oceanic and terrestrial carbon cycle processes linked with millennial-scale changes in atmospheric CO₂. However, the interpretation of δ¹³ CO₂ is not straight-forward. Using carbon isotope-enabled versions of the LOVECLIM and Bern3D models, we perform a set of sensitivity experiments in which the formation rates of North Atlantic Deep Water (NADW), North Pacific Deep Water (NPDW), Antarctic Bottom Water (AABW), and Antarctic Intermediate Water (AAIW) are varied. We study the impact of these circulation changes on atmospheric δ¹³ CO₂ as well as on the oceanic δ¹³ CO₂ distribution. In general, we find that the formation rates of AABW, NADW, NPDW, and AAIW are negatively correlated with changes in δ¹³ CO₂: namely, strong oceanic ventilation decreases atmospheric δ¹³ CO₂. However, since large-scale oceanic circulation reorganizations also impact nutrient utilization and the Earth’s climate, the relationship between atmospheric δ¹³ CO₂ levels and ocean ventilation rate is not unequivocal. In both models atmospheric δ¹³ CO₂ is very sensitive to changes in AABW formation rates: increased AABW formation enhances the transport of low δ¹³ CO₂ waters to the surface and decreases atmospheric δ¹³ CO₂. By contrast, the impact of NADW changes on atmospheric δ¹³ CO₂ is less robust and might be model dependent. This results from complex interplay between global climate, carbon cycle, and the formation rate of NADW, a water body characterized by relatively high δ¹³ CO₂.

Three Experimental Approaches to Measure the Social Context Dependence of Prejudice Communication and Discriminatory Behavior

Empirical research on discrimination is faced with crucial problems stemming from the specific character of its object of study. In democratic societies the communication of prejudices and other forms of discriminatory behavior is considered socially undesirable and depends on situational factors such as whether a situation is considered private or whether a discriminatory consensus can be assumed. Regular surveys thus can only offer a blurred picture of the phenomenon. But also survey experiments intended to decrease the social desirability bias (SDB) so far failed in systematically implementing situational variables. This paper introduces three experimental approaches to improve the study of discrimination and other topics of social (un-)desirability. First, we argue in favor of cognitive context framing in surveys in order to operationalize the salience of situational norms. Second, factorial surveys offer a way to take situational contexts and substitute behavior into account. And third, choice experiments – a rather new method in sociology – offer a more valid method of measuring behavioral characteristics compared to simple items in surveys. All three approaches – which may be combined – are easy to implement in large-scale surveys. Results of empirical studies demonstrate the fruitfulness of each of these approaches.